检索结果-内蒙古大学图书馆

14th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering, QR2MSE 2024

作者： Tao, Yulong Wang, Jun Wang, Kai School of Computer Science and Technology Shenyang University of Chemical Technology Shenyang China Key Laboratory of Intelligent Technology for Chemical Process Industry Liaoning Province Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Robotics and Artificial Intelligence Manufacturing Innovation Institute Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781837242672

The lithium-ion battery is increasingly critical in the fields of electric vehicles and sustainable energy. Accurate prediction of the Remaining Useful Life (RUL) of lithium-ion batteries is essential to mitigate risks and minimize potential losses. This paper introduces a novel fusion algorithm, FPSOGWO, which combines Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO) with an enhanced Circle chaos strategy and a random adaptive weighting strategy. The FPSOGWO algorithm, integrated with Support Vector Regression (FPSOGWO-SVR), was utilized to predict the RUL of health factors in lithium batteries. Compared to other optimization algorithms, FPSOGWO exhibits superior optimization speed and value, effectively overcoming issues of local optimality. Specifically, when benchmarked against the Whale Optimization Algorithm-SVR (WOA-SVR), the R-Square values of FPSOGWO-SVR showed improvements of 15.62%, 1.28%, 5.67%, and 10.65% across four different types of batteries. Experimental results demonstrate that FPSOGWO-SVR provides more accurate RUL predictions for lithium batteries, highlighting its potential for broader application in battery health management systems. © The Institution of Engineering & Technology 2024.

关键词： Support vector regression

来源：评论

学校读者我要写书评

暂无评论

Natural Gas Load Forecasting Based on Multi-Stage Model Identification 14

Natural Gas Load Forecasting Based on Multi-Stage Model Iden...

引用

14th IEEE International Conference on Cyber Technology in Automation, control, and Intelligent systems, CYBER 2024

作者： Zhang, Pengbin Wang, Hongrui Xing, Kunpeng Yuan, Mingzhe Shenyang Institute of Automation Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang110016 China Chinese Academy of Sciences Key Laboratory of Networked Control System Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Guangzhou Institute of Industrial Intelligence Guangzhou511458 China China Nuclear Power Engineering Co. Ltd. Shenzhen518124 China

ISBN: (纸本)9798331506056

Natural gas load forecasting is crucial for the safe operation of urban natural gas. Based on the system identification method, the short-term natural gas load forecasting is studied in the paper. Employing a multi-stage identification framework, the initial values of the model parameters using the least squares and the instrumental variables method, while the model parameters are further optimized by the prediction error method to improve the accuracy of the model identification. The proposed method is validated by the simulation based on the public natural gas data in the U.S., demonstrating the algorithm's effectiveness in forecasting the daily natural gas load effectively. © 2024 IEEE.

关键词： Prediction models

来源：评论

学校读者我要写书评

暂无评论

TASF: Terrestrial-Aerial Synergistic Framework for a New Generation of Intelligent Transportation 27

TASF: Terrestrial-Aerial Synergistic Framework for a New Gen...

引用

27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Wang, Cong Nie, Dujun Zhang, Ruijun Teng, Siyu Chen, Long Institute of Automation Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Hong Kong Baptist University Kowloon Hong Kong Waytous Inc. Beijing China Chinese Academy of Sciences State Key Laboratory of Multimodal Artificial Intelligence Systems The State Key Laboratory of Management and Control for Complex Systems Beijing100190 China Shenzhen518107 China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an710049 China

ISBN: (纸本)9798331505929

Terrestrial-Aerial Synergistic Framework (TASF) represents a novel approach to intelligent transportation, integrating terrestrial and aerial vehicles to enhance urban transportation efficiency and capacity. In this paper, we offer an in-depth analysis of TASF, emphasizing its innovative applications in urban transportation, parcel delivery, and emergency response services. TASF incorporates a five-layer architecture comprising perception, communication, planning, control, and interaction. With the five-layer architecture, TASF can achieve effective collaboration among terrestrial and aerial vehicles, encompassing two principal features: terrestrial-aerial synergistic parallel perception and multi-agent parallel management. Parallel perception results from fusing Bird's Eye View (BEV) representations from Unmanned Aerial Vehicles (UAVs) and Unmanned Ground Vehicles (UGVs), whereas decentralized multi-agent management employs foundational models to enhance decision-making capabilities. Additionally, we consider challenges and potential solutions related to TASF, including safety, reliability, energy efficiency, management and integration. TASF marks a paradigm-shifting leap in the realm of intelligent transportation systems, providing a scalable and efficacious solution tailored to the dynamic requirements of urban mobility and emergency services. © 2024 IEEE.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

Insulators Defect Detection for Power Grid Based on Improved Yolov7 Algorithm 13

Insulators Defect Detection for Power Grid Based on Improved...

引用

13th International Conference on Intelligent control and Information Processing, ICICIP 2025

作者： Zhang, Zhiwei Zhuang, Yan Liang, Zhida Kong, Shuai Zhu, Shengyi School of Control Science and Engineering Dalian University of Technology Dalian China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Special Equipment Safety Testing Technology of Zhejiang Province Zhejiang Academy of Special Equipment Science Hangzhou China

ISBN: (纸本)9798331516147

High-current out-of-phase closed bus is an essential link in the transmission of electric energy and is widely used in thermal power stations, hydropower stations and nuclear power plants. Although these busbars have the advantages of excellent dustproof effect and strong magnetic shielding, they are susceptible to insulator aging and damage in long-term operation, posing a potential safety risk to the power grid. Due to the enclosed space inside the bus and the complexity of external maintenance tasks, manual inspection has problems such as inefficiency and low safety. In order to solve these problems, this paper proposes an improved detection algorithm based on Yolov7 for insulator defect detection in hydropower station scenarios. Because of the particularity of Yolov7 network structure and application scenarios, this paper proposes a Channel Feature Enhancement module to enhance the channel representation ability of the network. In addition, an Edge Feature Enhancement module is introduced to improve the boundary detection of insulators by enhancing the contrast between the target and the background. Considering the limitations of existing studies in specific scenarios and the scarcity of dataset, this paper constructs and accurately annotates an insulator defect detection dataset applied to hydropower station scenarios. Experimental results show that the improved-Yolov7-tiny algorithm in this paper achieves a balance between accuracy and inference speed. © 2025 IEEE.

关键词： Magnetic shielding

来源：评论

学校读者我要写书评

暂无评论

Global-state-Free Obstacle Avoidance for Quadrotor control in Air-Ground Cooperation

引用

IEEE robotics and Automation Letters 2025年第7期10卷 6688-6695页

作者： Zhang, Baozhe Chen, Xinwei Chen, Qingcheng Xu, Chao Gao, Fei Cao, Yanjun Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber- Systems and Control Hangzhou310027 China Zhejiang University Huzhou Institute Huzhou313000 China Shanghai Institute of Special Equipment Inspection & Technical Research Shanghai200062 China

CoNi-MPC [1] provides an efficient framework for UAV control in air-ground cooperative tasks by relying exclusively on relative states, eliminating the need for global state estimation. However, its lack of environmental information poses significant challenges for obstacle avoidance. To address this issue, we propose a novel obstacle avoidance algorithm, Cooperative Non-inertial frame-based Obstacle Avoidance (CoNi-OA), designed explicitly for UAV-UGV cooperative scenarios without reliance on global state estimation or obstacle prediction. CoNi-OA uniquely utilizes a single frame of raw LiDAR data from the UAV to generate a modulation matrix, which directly adjusts the quadrotor's velocity to achieve obstacle avoidance. This modulation-based method enables real-time generation of collision-free trajectories within the UGV's non-inertial frame, significantly reducing computational demands (less than 5 ms per iteration) while maintaining safety in dynamic and unpredictable environments. The key contributions of this work include: (1) a modulation-based obstacle avoidance algorithm specifically tailored for UAV-UGV cooperation in non-inertial frames without global states;(2) rapid, real-time trajectory generation based solely on single-frame LiDAR data, removing the need for obstacle modeling or prediction;and (3) adaptability to both static and dynamic environments, thus extending applicability to featureless or unknown scenarios. © 2016 IEEE.

关键词： Quadrotors Collision avoidance Dynamics Autonomous aerial vehicles Trajectory Laser radar Air to ground communication Real-time systems Modulation Dynamical systems

来源：评论

学校读者我要写书评

暂无评论

Multimodal Perception for Indoor Mobile robotics Navigation and Safe Manipulation

引用

IEEE Transactions on Cognitive and Developmental systems 2024年

作者： Zhang, Yinlong Liu, Yuanhao Liu, Shuai Liang, Wei Wang, Chu Wang, Kai Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang Institute of Automation Shenyang110016 China Chinese Academy of Sciences State Key Laboratory of Robotics Shenyang Institute of Automation Shenyang110016 China University of Chinese Academy of Sciences Beijing101408 China

Indoor mobile robotics (IMR) has gained significant attention due to its potential applications in various domains, such as healthcare, logistics, and domestic assistance. However, navigating through indoor environments and performing safe manipulations still pose intractable challenges in terms of navigation accuracy and obstacle avoidance. To solve these issues, this paper presents an Artificial Intelligence (AI) embodied multimodal perception framework for IMR intelligent navigation and safe manipulation. To ensure the navigation accuracy and robustness, we employ the complementary forward RGB camera, downward QR vision sensor, and wheel encoder measurements in a unified framework. The visual residuals and wheel odometry residuals are jointly minimized to estimate the robot states. To guarantee the safety of robotic manipulation tasks, we have developed an AI model that integrates transformer network with convolutional neural network, to associate the long-range RGB & depth patches and aggregate the multi-scale obstacle features, enabling the precise detection and segmentation of obstacles in RGB-D images. Afterwards, the depths of detected obstacles are regressed, providing the robot with crucial information for collision avoidance. Eventually, we design a refined robot manipulation system that dynamically adjusts the robot behavior to ensure effective collision avoidance and to minimize potential damage to its mechanical components by constantly evaluating the spatial relationships between the robot and its surroundings. By incorporating advanced obstacle detection and the avoidance mechanism, mobile robots can navigate reliably in indoor environments with a reduced risk of collisions and real-time decision making. The presented method has been evaluated on the developed IMR platform. On the collected dataset, the estimated IMR absolute position and orientation errors are less than 0.18m and 5° respectively. Besides, it achieves 89% mAP on obstacle detection. T

关键词： Image segmentation

来源：评论

学校读者我要写书评

暂无评论

Optimization of Milling Robot Trajectory Based on Whale Optimization Algorithm 3rd

Optimization of Milling Robot Trajectory Based on Whale Opti...

引用

3rd International Conference on Artificial Intelligence, robotics, and Communication, ICAIRC 2023

作者： Zhou, Yang Li, Qingxin Sun, Yong Software College Shenyang University of Technology Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang110016 China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China

ISBN: (纸本)9789819721993

In response to the problem of vibration and low work efficiency during robot milling, taking into account the work indicators of milling time and stability, combined with the kinematic constraints of the robotic arm, the time impact optimization problem is transformed into a multi-objective optimization problem. The paper proposes an improved whale optimization algorithm, which introduces a differential mutation strategy to improve the problem of traditional whale algorithms easily getting stuck in local optima. Compared with traditional whale optimization algorithms, the improved whale algorithm significantly improves the convergence speed and accuracy during the milling process. Finally, it is verified by a solid robot. The results showed that the pulse value of the planned trajectory was reduced by up to 99.76%, and the efficiency was improved by 47.62%, effectively avoiding robot vibration during the milling process. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Multiobjective optimization

来源：评论

学校读者我要写书评

暂无评论

An Optimal control Based Trajectory Planning Method for Cooperative Merging Maneuvers 3

An Optimal Control Based Trajectory Planning Method for Coop...

引用

3rd International Symposium on Intelligent robotics and systems, ISoIRS 2023

作者： Wang, Qi Ge, Hao Duan, Xuting Zhou, Jianshan School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control State Key Laboratory of Air Traffic Management System and Technology Beijing China Nanjing Research Institute of Electronic Engineering State Key Laboratory of Air Traffic Management System and Technology Nanjing China School of Transportation Science and Engineering Beihang University State Key Lab of Intelligent Transportation System Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control Beijing China

ISBN: (纸本)9798350339963

Due to the prediction errors and diverse driving styles of surrounding vehicles, traffic congestion and even accidents can occur in the traffic bottleneck area where vehicles merge into the main road. To ensure that connected and automated vehicles (CAVs) can quickly and efficiently merge into the main road, this paper proposes a cooperative trajectory planning method based on optimal control for vehicle cut-in scenarios. A optimal control model is constructed, and a quintic polynomial is used to generate the initial solution of the optimal control problem to accelerate the solution process and improve the success rate. Finally, The obtained merging trajectory is then synchronized with the movement of vehicles on the main road to optimize their actions and ensure a safe merging process. Joint simulation with Robot Operating System (ROS) and RVIZ is utilized, and the results show that the proposed algorithm can quickly obtain cooperative results, the locally successful merging trajectory meets the requirements of smoothness and safety, and if the solution does not allow merging, the merging vehicle is instructed to terminate the execution. © 2023 IEEE.

关键词： Trajectories

来源：评论

学校读者我要写书评

暂无评论

A Relational Retrieval Model for Industrial Production systems 2

A Relational Retrieval Model for Industrial Production Syste...

引用

2nd International Conference on Electrical Engineering and Mechatronics Technology, ICEEMT 2022

作者： Liu, Yang Zhang, Tianshi Shenyang Institute of Automation Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China

ISBN: (数字)9781665459280

ISBN: (纸本)9781665459280

Industrial big data analysis is an important approach to explore the essence of industrial production processes. Traditional keyword retrieval and semantic retrieval are difficult to adapt to the industrial manufacturing systems with the characteristics of strong coupling of business associations. Therefore, according to the characteristics of the association in the industrial production system, an association retrieval model for the industrial production system is proposed in this paper. Firstly, the industrial Internet of things system is analyzed and abstracted, and the key factors of correlation retrieval are derived;then through the analysis of the relationship between key factors, the invalid relationship is screened out, the correlation relationship with practical significance is obtained, and the establishment of the relevance retrieval model is completed. Finally, the feasibility and effectiveness of the association retrieval model are verified by actual industrial scene data. © 2022 IEEE.

关键词： Manufacture

来源：评论

学校读者我要写书评

暂无评论

Design of an Acupuncture Robot with Vision-Guided Positioning and Force Compliance control 6

Design of an Acupuncture Robot with Vision-Guided Positionin...

引用

6th International Symposium on robotics and Intelligent Manufacturing Technology, ISRIMT 2024

作者： Chen, Zhengtao Li, Bochen Feng, Yanhao Chen, Genliang Wang, Hao Shanghai Jiao Tong University Shanghai Key Laboratory of Digital Manufacturing for Thin-Walled Structures Shanghai China Meta Robotics Institute Shanghai Jiao Tong University Shanghai China Shanghai Jiao Tong University State Key Laboratory of Mechanical Systems and Vibration Shanghai China

ISBN: (纸本)9798331528942

Acupuncture is a classic treatment method in traditional Chinese medicine. At present, it mainly relies on experienced doctors for manual treatment. The inheritance of skills and the guarantee of treatment effects require lots of training to guarantee, which is far from meeting needs. In this paper, an acupuncture robot system was designed to ensure the accuracy of acupoint positioning and safety during needle insertion, making robot-assisted acupuncture treatment a feasible alternative. The acupuncture robot has an acupoint marking and visual guidance system. According to the location of the acupoints accurately marked by the doctor on the patient's 3D reconstructed model, the robot is accurately guided to perform acupuncture treatment. The positioning error of this system is within 1.5mm, which meets the needs of acupuncture. In addition, a terminal needle-punching manipulator with compliant needle insertion force control, needle insertion depth feedback, and continuous needle insertion functions is designed. Through the closed-loop control of the needle-punching manipulator, the safety and accuracy of the acupuncture robot are fully guaranteed. Finally, an acupuncture experiment was designed to verify the accuracy and safety of the acupuncture robot. © 2024 IEEE.

关键词： Acupuncture

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：